What challenges did AstraZeneca face before AI implementation?

Clinical trial workflows are complex and require fast access to reliable insights across structured and unstructured data. Teams across clinical, regulatory, safety, and quality functions need quicker retrieval of trusted information to support development decisions.

What was the impact of the AI solution?

The assistant enables teams to access trial-related insights in seconds. The article presents the solution as already in production use across critical development workflows.

Source

ProductionEvidence: Medium55/100

AstraZeneca on AWS: Amazon Bedrock agentic Development Assistant for clinical trials

Use case typeDrug discoveryUpdated Jun 13, 2026

AstraZeneca is a global, science-led biopharmaceutical company focused on discovery, development and commercialization of prescription medicines. The company uses AWS to support research through commercialization, and specifically applies Amazon Bedrock to accelerate clinical trials by combining structured and unstructured data. An agentic AI-powered Development Assistant gives clinical, regulatory, safety, and quality teams conversational access to trusted insights in seconds.

Organization: AstraZeneca
Industry: Pharma
Location: United Kingdom
Published: May 2026

Planned next steps

The goal is to accelerate drug development and advance AstraZeneca's clinical trials transformation.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: AstraZeneca
Provider: AWS
Maturity: Production
Linked source: AWS Customer Story

The article presents the solution as already in production use across critical development workflows

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 5

1Clinical trials
2Drug development
3Research assistant

AstraZeneca uses Amazon Bedrock with text-to-SQL and retrieval-augmented generation (RAG).
The solution is an agentic AI-powered Development Assistant that provides conversational access to insights.
The implementation is described as modular and multi-agent, combining data modalities and improving data reliability.

Technologies

Amazon Bedrock Retrieval-Augmented Generation RAG text-to-SQL Agentic AI

The assistant enables teams to access trial-related insights in seconds.
The article presents the solution as already in production use across critical development workflows.

Architecture

AstraZeneca's Development Assistant uses Amazon Bedrock with text-to-SQL and retrieval-augmented generation to merge structured and unstructured data. The article describes an agentic, modular multi-agent design that exposes trusted insights through a conversational interface for clinical development teams.

Sources & evidence1

Evidence: Medium55/100Evidence strength